Earticle

초록

영어

Image mining is used to mine knowledge from large image databases. Image segmentation, image compression, image clustering, image classification and image retrieval are significant image mining tasks. Face detection methods are used to identify the similar faces from the large collection of facial images. It has numerous computer vision applications and it has many research challenges such as rotation, scale, pose and illumination variation. Facial expression is defined as the position of the muscles beneath the skin of the face and it is a form of nonverbal communication. Facial expressions are the expression which shows the emotions and different feelings of human beings. Different facial expressions are sad, happy, fear, normal, surprise and angry. In this research work facial expressions are classified by using the optimization algorithms. PSO with LIBSVM algorithm is proposed for facial expression classification and the performance of this algorithm is compared with the existing BAT algorithm. The results of the existing and proposed algorithms are analyzed based on the two performance factors; they are classification accuracy and execution time. From the experimental results, we observed that the proposed PSO with LIBSVM algorithm has produced good results compared to existing BAT algorithm. This work is implemented in MATLAB 7.0.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Proposed Methodology
 4. Experimental Results
 References

키워드

저자

• S. Vijayarani [ Assistant Professor, M.Phil Research Scholar, Department of Computer Science, Bharathiar University, Coimbatore,Tamilnadu,India ]
• S. Priyatharsini [ Assistant Professor, M.Phil Research Scholar, Department of Computer Science, Bharathiar University, Coimbatore,Tamilnadu,India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605